In a semiconductor manufacturing apparatus, alignment of a wafer and a reticle is carried out before a reticle pattern is projected onto the wafer to expose the wafer. In order to perform such alignment, usually, a digital image (referred to as an “observed image” below) centered on a mark on the wafer is loaded into the semiconductor manufacturing apparatus using an image input unit, such as a CCD, and the position of the mark in the observed image is detected using a pattern recognition technique. The detection procedure is divided into two parts, namely, first narrowing down a coarse position from the overall observed image and then detecting the precise position from the narrowed-down area.
The present invention focuses particularly on the narrowing down of the coarse position (referred to as “mark position detection” below) from the overall observed image in the detection part of the procedure.
Ordinarily, a pattern recognition technique is used in mark position detection. An evaluation value at each position of the observed image is calculated using this pattern recognition technique and the position having the largest evaluation value is adopted as the mark position.
Methods of performing pattern recognition used, therefore, include (i) a vector correlation method (see the specification of Japanese Patent Application Laid-Open No. 2001-195583) of calculating a degree of correlation of an image near a position of interest (this image shall be referred to as a “partial image” below) using edge information of a mark as a template, (ii) a cross-correlation method using luminance values of the image of the designed mark and of the observed image, and (iii) a cross-correlation method (referred to as a “Fourier phase correlation method” below) that uses an image (referred to as a “Fourier phase image” below), which is obtained by subjecting the image of the designed mark to a Fourier transform and then subjecting only the phase components thereof to an inverse Fourier transform, and the Fourier phase image of the observed image.
In a case where mark position detection is carried out using a pattern recognition technique of the kind cited as (i) to (iii) above, a rate of detection declines markedly owing to a decline in the image quality of the observed image. In order to expose a wafer to the same pattern in a semiconductor manufacturing apparatus, the same image should be captured as the observed image. However, owing to process fluctuations and illumination conditions, there are instances where (1) the average luminance of each partial image differs from one observed image to another, and (2) the difference between the amplitude of the mark signal and the amplitude of a noise signal diminishes.
Whether or not the prior art has robustness against the decline in image quality mentioned in (1) and (2) above will be discussed below in consideration of the theoretical strong points and shortcomings of the prior art.
First, a fundamental strong point of the vector correlation method is that since the strength of an edge at a determined position in the partial image is normalized to calculate the degree of correlation, it is possible to recognize the shape of a template not easily affected by the average luminance of the partial image. For example, as shown in FIG. 10, if a degree of correlation with respect to an image A of average luminance a and an image B of average luminance b obtained by changing the contrast of the image A is calculating using a template image T, the image A and the image B will both have the same value. FIGS. 11A and 11B illustrate examples of partial images. FIG. 12 illustrates an example of an observed image that includes partial images obtained by lowering the contrasts of the partial images in FIGS. 11A and 11B, to reduce the average luminance. FIG. 13 illustrates an example of an observed image that includes a partial image, the average luminance of which has been lowered by reducing the contrast of image in FIG. 11A, and the partial image in FIG. 11B. When a degree of correlation with respect to FIGS. 12 and 13 is calculated using a template image of FIG. 14, the values of the partial image A in FIG. 12 and partial image A in FIG. 13 are the same, and the values of the partial image B in FIG. 12 and partial image B in FIG. 13 are the same. In view of this fact, the vector correlation method is such that even in a case wherein the average luminance of each partial image differs from one observed image to another mentioned in (1) above, the same degree of correlation can be calculated stably if the shapes are the same.
Next, a fundamental shortcoming of the vector correlation method is that since the edge position of the mark is decided at only a plurality of points beforehand and a degree of correlation of the partial image calculated, there are cases where a partial image, in which an edge exists at a position other than the positions of the decided points, is mistaken as the mark. For example, a degree of correlation of a partial image S is calculated in advance using edge information at positions 1, 2, 3, 4 of a template image T in FIG. 15. The degree of correlation of the partial image S and the mark image is the same. Further, in a case wherein the difference between the amplitude of the mark signal and the amplitude of the noise signal diminishes as mentioned at (2) above, there are instances where the difference between edge information of the mark and edge information of a noise portion vanishes, thereby resulting in erroneous detection. For example, in a case wherein use is made of edge information at positions 1, 2, 3, 4 of the template image T in FIG. 15, there is almost no difference between the degrees of correlation of the mark image M and noise image N.
The fundamental strong point of the cross-correlation method and Fourier phase correlation method is that since the degree of correlation is calculated using luminance information of the entirety of the partial image, the degree of correlation of a partial image in which only the template image is present becomes higher than that of a partial image in which the template image and portions that do not exist in the template image are present at the same time, and, therefore, it is possible to distinguish between them. For example, if the template image T is used in FIG. 15, then the degree of correlation of the mark image will be higher than the degree of correlation of the partial image S.
However, a fundamental shortcoming of the cross-correlation method and Fourier phase correlation method is that since the degree of correlation is calculated using a variation in the luminance of the partial image, the degree of correlation is influenced by the average luminance of one partial image to another. For example, if FIG. 14 is used as the template image, there will be cases wherein the degree of correlation of the partial image A of high average luminance in the observed image of FIG. 12 will be higher than that of the partial image B of low average luminance, and cases wherein the degree of correlation of the partial image B of high average luminance in the observed image of FIG. 13 will be higher than that of the partial image A of low average luminance. This means that in a case wherein the average luminance of each partial image differs from one observed image to another in (1) above, erroneous detection may occur. Further, if the difference between the amplitude of the mark signal and the amplitude of the noise signal diminishes in (2) above, the difference between the mark image and the noise image becomes small and, moreover, the average luminance of the mark image and that of the noise image approach each other. Consequently, there are cases wherein erroneous detection occurs. For example, if the template image T of FIG. 15 is used, there is almost no difference between the degrees of correlation of the mark image M and noise image N in FIG. 16.
The following problems (A) to (C) arise owing to the fundamental shortcomings mentioned above:
(A) With the vector correlation method (i), there are instances where a partial image in which an edge exists at a position other than at the positions of a plurality of points decided in advance is erroneously detected as the mark.
(B) With the cross-correlation method (ii) or Fourier phase correlation method (iii), erroneous detection may occur if the average luminance of the mark image is lower than that of other portions.
(C) Further, a problem common to the vector correlation method, cross-correlation method and Fourier phase correlation method is that if the amount of noise in the observed image is great, the difference between the evaluation values of the mark and other portions diminishes, and may result in erroneous detection.